Automate Your Accounts Receivable Collections with Custom AI

Most SMBs use the built-in reminder features in QuickBooks or Xero. These tools send generic templates on a fixed schedule. They cannot escalate follow-ups based on the invoice value, the customer's payment history, or parse an email reply like, “I can pay this next Friday.” This rigidity forces your finance team to manually track and personalize communication for all high-value accounts.

Third-party collection tools like Chaser or Upflow offer more advanced reminder sequences but still operate on fixed rules. They cannot manage complex scenarios, such as an invoice dispute that needs routing to a specific account manager or a customer who requires a unique PO number on every communication. The data sync is often hourly, not real-time, which can result in an automated reminder being sent minutes after a customer has already paid.

For example, a 25-person services firm has a client who requires invoices to reference a specific PO number from their procurement system. The standard QuickBooks reminder does not include this custom field. An AR specialist spends hours every week manually cross-referencing POs, editing email templates, and sending follow-ups. A $20,000 invoice can be delayed 30 days simply because the automated reminder lacked the required PO number, directly impacting cash flow.

The structural problem is that off-the-shelf platforms are built for generic accounting, not intelligent collections. Their data models are fixed, so you cannot add customer-specific fields and have the automation engine use them. Their logic is linear, preventing the system from reading a customer's email, checking Stripe for a partial payment, and then deciding on the next best action. This forces your most expensive resource, your team's time, onto low-value, repetitive tasks.

The engagement begins by mapping your end-to-end accounts receivable process. Syntora gains read-only access to your accounting software, payment processor, and CRM to audit the existing data flow. We identify the specific exceptions and communication patterns that current tools miss. This audit produces a technical blueprint for an automation system designed for your exact business logic.

We built our own financial systems connecting Plaid, Stripe, and a PostgreSQL database, so we understand the architecture. For your AR system, we would deploy a central FastAPI service on AWS Lambda to act as the control center. The service uses the QuickBooks API to pull invoice data, the Claude API to analyze customer email replies for payment intent, and the Stripe API to generate payment links or verify payments. This serverless architecture keeps hosting costs under $50 per month.

The delivered system runs automatically, sending context-aware reminders that include customer-specific data like PO numbers. When a customer replies with a question or dispute, the AI classifies the email and can create a task in Asana or Slack for human review. You receive a simple dashboard showing aging AR, predicted payment dates, and system activity. You own all the Python code, which is deployed in your cloud account, not ours.